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Personalizable Pen-Based Interface Using Life-Long Learning
Abstract : In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a fuzzy adaptation method in order to learn and maintain the model. We use this method to build an evolving handwritten gesture recognition system, that can be integrated into an application to provide personalization capabilities. Experiments on an on-line gesture database were performed by considering various user personalization scenarios. The experiments show that the proposed evolving gesture recognition system continuously adapts and evolve according to new data of learned classes, and remains robust when introducing new unseen classes, at any moment during the lifelong learning process.
Cited literature [12 references]
https://hal.archives-ouvertes.fr/hal-00582441
Contributor : Solen Quiniou Connect in order to contact the contributor
Submitted on : Friday, April 1, 2011 - 2:50:17 PM
Last modification on : Thursday, January 7, 2021 - 4:11:51 PM
Long-term archiving on: : Saturday, July 2, 2011 - 2:46:20 AM
Contributor : Solen Quiniou Connect in order to contact the contributor
Submitted on : Friday, April 1, 2011 - 2:50:17 PM
Last modification on : Thursday, January 7, 2021 - 4:11:51 PM
Long-term archiving on: : Saturday, July 2, 2011 - 2:46:20 AM
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almaksour10personalizable.pdf
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